947 resultados para 300602 Tree Improvement (Selection, Breeding and Genetic Engineering)


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Participatory plant breeding (PPB) has been suggested as an effective alternative to formal plant breeding (FPB) as a breeding strategy for achieving productivity gains under low input conditions. With genetic progress through PPB and FPB being determined by the same genetic variables, the likelihood of success of PPB approaches applied in low input target conditions was analyzed using two case studies from FPB that have resulted in significant productivity gains under low input conditions: (1) breeding tropical maize for low input conditions by CIMMYT, and (2) breeding of spring wheat for the highly variable low input rainfed farming systems in Australia. In both cases, genetic improvement was an outcome of long-term investment in a sustained research effort aimed at understanding the detail of the important environmental constraints to productivity and the plant requirements for improved adaptation to the identified constraints, followed up by the design and continued evaluation of efficient breeding strategies. The breeding strategies used differed between the two case studies but were consistent in their attention to the key determinants of response to selection: (1) ensuring adequate sources of genetic variation and high selection pressures for the important traits at all stages of the breeding program, (2) use of experimental procedures to achieve high levels of heritability in the breeding trials, and (3) testing strategies that achieved a high genetic correlation between performance of germplasm in the breeding trials and under on-farm conditions. The implications of the outcomes from these FPB case studies for realizing the positive motivations for adopting PPB strategies are discussed with particular reference for low input target environment conditions.

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Most sugarcane breeding programs in Australia use large unreplicated trials to evaluate clones in the early stages of selection. Commercial varieties that are replicated provide a method of local control of soil fertility. Although such methods may be useful in detecting broad trends in the field, variation often occurs on a much smaller scale. Methods such as spatial analysis adjust a plot for variability by using information from immediate neighbours. These techniques are routinely used to analyse cereal data in Australia and have resulted in increased accuracy and precision in the estimates of variety effects. In this paper, spatial analyses in which the variability is decomposed into local, natural, and extraneous components are applied to early selection trials in sugarcane. Interplot competition in cane yield and trend in sugar content were substantial in many of the trials and there were often large differences in the selections between the spatial and current method used by the Bureau of Sugar Experiment Stations. A joint modelling approach for tonnes sugar per hectare in response to fertility trends and interplot competition is recommended.

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To determine the potential for rootstocks to improve avocado quality, 'Hass' fruit from trees on seedling 'Velvick' (SV), clonal 'Velvick' (CV) or clonal 'Duke 7' (CD) rootstocks were harvested in 1999 and 2000, ripened at 20 C immediately after harvest (non-stored) or stored at 5 C for four weeks (stored), and then fruit quality and mineral concentrations determined. In 2000, non-stored CV fruit had lower severity of body rots (5% of flesh volume affected, caused mainly by Colletotrichum gloeosporioides) than CD fruit (20%), while body rots severity in stored CV fruit was 20% compared with 38% in stored CD fruit. Stored CV fruit had less severe diffuse discoloration (3% and 9% in 1999 and 2000, respectively) than CD fruit (7% and 20%, respectively). Stored CV fruit also had less severe vascular browning (19%) than CD fruit (33%) in 2000. In both seasons, CV fruit had 15-19% higher flesh calcium concentrations, 17-22% higher flesh boron concentrations, and 14-15% lower flesh nitrogen concentrations than CD fruit. In 2000, CV fruit also had 27% more skin calcium and 14% less skin nitrogen than CD fruit. There were no effects of rootstock on yield, canopy volume, measured length of non-suberized roots, average fruit weight, fruit length: width ratio, skin thickness, dry matter, proportion of the fruit skin purple-black when ripe, or seed mass: fruit weight ratio. These results suggest that there is potential to improve 'Hass' avocado quality through rootstock selection, and that tree and fruit mineral concentrations have a role in this relationship.

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Functional genomics is the systematic study of genome-wide effects of gene expression on organism growth and development with the ultimate aim of understanding how networks of genes influence traits. Here, we use a dynamic biophysical cropping systems model (APSIM-Sorg) to generate a state space of genotype performance based on 15 genes controlling four adaptive traits and then search this spice using a quantitative genetics model of a plant breeding program (QU-GENE) to simulate recurrent selection. Complex epistatic and gene X environment effects were generated for yield even though gene action at the trait level had been defined as simple additive effects. Given alternative breeding strategies that restricted either the cultivar maturity type or the drought environment type, the positive (+) alleles for 15 genes associated with the four adaptive traits were accumulated at different rates over cycles of selection. While early maturing genotypes were favored in the Severe-Terminal drought environment type, late genotypes were favored in the Mild-Terminal and Midseason drought environment types. In the Severe-Terminal environment, there was an interaction of the stay-green (SG) trait with other traits: Selection for + alleles of the SG genes was delayed until + alleles for genes associated with the transpiration efficiency and osmotic adjustment traits had been fixed. Given limitations in our current understanding of trait interaction and genetic control, the results are not conclusive. However, they demonstrate how the per se complexity of gene X gene X environment interactions will challenge the application of genomics and marker-assisted selection in crop improvement for dryland adaptation.

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Phytophthora root rot, caused by Phytophthora medicaginis, is a major limitation to lucerne ( Medicago sativa L.) production in Australia and North America. Quantitative trait loci (QTLs) involved in resistance to P. medicaginis were identified in a lucerne backcross population of 120 individuals. A genetic linkage map was constructed for tetraploid lucerne using 50 RAPD ( randomly amplified polymorphic DNA), 104 AFLP (amplified fragment length polymorphism) markers, and one SSR ( simple sequence repeat or microsatellite) marker, which originated from the resistant parent (W116); 13 markers remain unlinked. The linkage map contains 18 linkage groups covering 2136.5 cM, with an average distance of 15.0 cM between markers. Four of the linkage groups contained only either 2 or 3 markers. Using duplex markers and repulsion phase linkages the map condensed to 7 homology groups and 2 unassigned linkage groups. Three regions located on linkage groups 2, 14, and 18, were identified as associated with root reaction and the QTLs explained 6 - 15% of the phenotypic variation. The research also indicates that different resistance QTLs are involved in conferring resistance in different organs. Two QTLs were identified as associated with disease resistance expressed after inoculation of detached leaves. The marker, W11-2 on group 18, identified as associated with root reaction, contributed 7% of the phenotypic variation in leaf response in our population. This marker appears to be linked to a QTL encoding a resistance factor contributing to both root and leaf reaction. One other QTL, not identified as associated with root reaction, was positioned on group 1 and contributed to 6% of the variation. This genetic linkage map provides an entry point for future molecular-based improvement of lucerne in Australia, and markers linked to the QTLs we have reported should be useful for marker-assisted selection for partial resistance to P. medicaginis in lucerne.

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New tools derived from advances in molecular biology have not been widely adopted in plant breeding for complex traits because of the inability to connect information at gene level to the phenotype in a manner that is useful for selection. In this study, we explored whether physiological dissection and integrative modelling of complex traits could link phenotype complexity to underlying genetic systems in a way that enhanced the power of molecular breeding strategies. A crop and breeding system simulation study on sorghum, which involved variation in 4 key adaptive traits-phenology, osmotic adjustment, transpiration efficiency, stay-green-and a broad range of production environments in north-eastern Australia, was used. The full matrix of simulated phenotypes, which consisted of 547 location-season combinations and 4235 genotypic expression states, was analysed for genetic and environmental effects. The analysis was conducted in stages assuming gradually increased understanding of gene-to-phenotype relationships, which would arise from physiological dissection and modelling. It was found that environmental characterisation and physiological knowledge helped to explain and unravel gene and environment context dependencies in the data. Based on the analyses of gene effects, a range of marker-assisted selection breeding strategies was simulated. It was shown that the inclusion of knowledge resulting from trait physiology and modelling generated an enhanced rate of yield advance over cycles of selection. This occurred because the knowledge associated with component trait physiology and extrapolation to the target population of environments by modelling removed confounding effects associated with environment and gene context dependencies for the markers used. Developing and implementing this gene-to-phenotype capability in crop improvement requires enhanced attention to phenotyping, ecophysiological modelling, and validation studies to test the stability of candidate genetic regions.

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The magnitude and nature of genotype-by-environment interactions (G×E) for grain yield (GY) and days to flower (DTF) in Cambodia were examined using a random population of 34 genotypes taken from the Cambodian rice improvement program. These genotypes were evaluated in multi-environment trials (MET) conducted across three years (2000 to 2002) and eight locations in the rainfed lowlands. The G×E interaction was partitioned into components attributed to genotype-by-location (G×L), genotype-by-year (G×Y) and genotype-by-location-by-year (G×L×Y) interactions. The G×L×Y interaction was the largest component of variance for GY. The G×L interaction was also significant and comparable in size to the genotypic component (G). The G×Y interaction was small and non significant. A major factor contributing to the large G×L×Y interactions for GY was the genotypic variation for DTF in combination with environmental variation for the timing and intensity of drought. Some of the interactions for GY associated with timing of plant development and exposure to drought were repeatable across the environments enabling the identification of three-target populations of environments (TPE) for consideration in the breeding program. Four genotypes were selected for wide adaptation in the rainfed lowlands in Cambodia.